Vetted MongoDB Professionals

“Backend/data engineer with experience at Nike building high-volume order orchestration and validation APIs using FastAPI microservices on AWS EKS with Kafka, Redis, and Postgres. Strong in production reliability (timeouts/retries/idempotency), GitOps (Argo CD) + Terraform deployments, and data pipelines (AWS Glue/S3), with hands-on incident ownership and legacy modernization into API-driven services.”

“Senior, product-focused engineer who has built real-time customer-facing web applications and a microservices backend (TypeScript/React/Node) using RabbitMQ, MongoDB, and Redis. Demonstrates strong operational maturity (idempotency, tracing/observability, backpressure) and built an internal console that became the primary tool for debugging, replaying jobs, and managing system behavior.”

Dennis Noto

Screened

Executive Technology & Security Leader specializing in FinTech, AI platforms, and enterprise modernization

Denver Metro Area36y exp

“Technology transformation leader who builds board-approved roadmaps and scales engineering orgs with strong Agile execution. Led large modernization efforts (e.g., Scottrade: 3,000 programs/4M LOC in 18 months) and scaled POCs into enterprise SaaS platforms using Docker, Kubernetes, Helm, and Terraform for high-concurrency workloads.”

Ravikanth Kasamsetty

Screened

Executive engineering leader specializing in AI, data platforms, and cloud SaaS

California, USA23y exp

“Senior engineering executive with a rare mix of VP-level people leadership and deep hands-on architecture across cloud-native and AI platforms. He led secure hybrid SaaS design at Promethium, built GenAI-powered analytics with LLMs/RAG, and translated customer needs into product wins including the largest deal in company history and a PLG motion that generated 100+ leads.”

“Senior engineering leader with a rare blend of deep platform/infrastructure expertise and large-scale people leadership, spanning hands-on cloud-native architecture through management of globally distributed organizations of up to roughly 180 engineers. Particularly strong in Kubernetes platform modernization, reliability engineering, and scaling high-throughput SaaS systems while aligning platform investments to customer and business outcomes.”

Xun He

Screened

Staff Software Engineer specializing in backend systems and security engineering

25y exp

“Senior backend/infrastructure engineer with experience at Microsoft, DocuSign, Pinterest, and Harness, focused on security and developer productivity systems. Stands out for building Pinterest's first vulnerability management platform from scratch for a 100,000-EC2 production environment and driving major performance gains, while also delivering CI/Docker infrastructure and Python test intelligence features shaped by customer demand.”

Yishi Wang

Screened

Junior Machine Learning & Data Science professional specializing in LLMs and analytics

Chicago, IL3y exp

“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”

“Engineering leader with a mix of large-scale platform experience at Microsoft and product/customer-facing work across GM, Panasonic, Acuity, and other environments. Stands out for combining people leadership with hands-on depth in accessibility, web performance at 120M+ MAU scale, and cross-functional delivery spanning enterprise permissions, e-commerce, AI, and automotive systems.”

Jiayi Zhang

Screened

Junior Full-Stack Engineer specializing in AI automation for FinTech and logistics

San Francisco, CA3y exp

“Full-stack product engineer focused on operational automation with AI in invoice, billing, and shipment workflows. Has shipped production systems using OpenAI APIs and AI agents that materially reduced manual work and cut bill transcription costs by 99%, while also improving UX through human-in-the-loop interfaces and performance tuning.”